In light of the myriad technological advancements that have characterized the previous decade, providing high security for computer systems and facilities has become a daunting challenge. Even as recent statistics are showing a decline in the overall violent crime rate, theft and more particularly technology related crime, has soared. The problem is costing insurance companies, and U.S. citizens, billions of dollars each year. Hackers who have successfully introduced computer viruses through email and other means have cost corporations millions if not billions of dollars in repair costs, lost work product and lost revenue. Because of this sophisticated criminal environment, many companies, government agencies and individuals alike have begun to view biometric security applications in a far more favorable light, however, biometric identification techniques (recognizing an individual based on a physiological metric), have yet to be employed either due to their complexity, invasiveness (lengthy recognition delays) or high cost.
There exists many methods for providing security against fraud and theft including conventional keys, remote keyless entry systems, key pad interfaces which require the user to enter a Personal Identification Number (PIN), alarm systems, magnetic card systems and proximity device systems. Similarly there exists many methods for the biometric identification of humans which includes facial image verification, voice recognition, iris scanning, retina imaging as well as fingerprint pattern matching.
Biometric verification systems work best when employed in a one-to-one verification mode (comparing one unknown biometric to one known biometric). When biometric verification is used in a one-to-many mode (comparing one unknown biometric to a database of known biometrics) such as one might employ in a facility security application, processing delays caused by the inefficiency of searching the entire database for a match are often unacceptable when the number of users exceeds 20 to 30 individuals. This makes most biometric applications unsuitable for larger user databases. In order to circumvent this limitation, a biometric verification algorithm is typically integrated with a non-biometric device such as a PIN keypad. The advantage to this arrangement is that a one-to-many verification scenario can be reduced to a one-to-one verification scenario by limiting the biometric comparison only to the data file associated with a particular PIN number. Thus, by inputting a PIN, the biometric algorithm is able to narrow its search within a much larger database to only one individual The disadvantage to this arrangement is of course the loss of the pure biometric architecture coupled with the inconvenience of having to administer and remember PIN numbers or maintain magnetic cards. In order for Biometric security systems to be unconditionally accepted by the marketplace, they must replace the more conventional security methods in biometric-only embodiments.
Iris and retina identification systems, although very accurate, are considered “invasive”, expensive and not practical for applications where limited computer memory storage is available. Voice recognition is somewhat less invasive, however it can require excessive memory storage space for the various voice “templates” and sophisticated recognition algorithms. All three of these technologies have processing delays associated with them that make their use in one-to-many verification applications inappropriate.
Face verification systems, although non-invasive with minimal processing delays, tend to be less accurate than the methods described above. Face recognition systems can be successfully implemented for one-to-many verification applications, however, because recognition algorithms such as principal component analysis exist which permit extremely rapid searches and ordering of large databases of facial images. Due to the abundant availability of extremely fast and inexpensive microprocessors, it is not difficult to create algorithms capable of searching through more than 20,000 facial images in less than one second.
Fingerprint verification is a minimally invasive and highly accurate way to identify an individual A fingerprint verification system utilizing an integrated circuit or optically based sensor can typically scan through a large database of users at the rate of approximately one comparison per 100 milliseconds. Although this delay is acceptable for small numbers of users, delays of several seconds can be incurred when the number of users exceeds 20 to 30 individuals. For example, for an extremely large user database of 2000 individuals and assuming 100 milliseconds processing delay per individual, a worst-case verification delay could be more than three minutes. This delay would clearly be unacceptable in all but the most tolerant security applications.
The prior references are abundant with biometric verification systems that have attempted to identify an individual based on one or more physiologic metrics. Some inventors have combined more than one biometric system in an attempt to increase overall accuracy of the verification event. One of the major problems that continues to impede the acceptance of biometric verification systems is unacceptable delays associated with one-to-many verification events. To date, the only attempt directed towards reducing these unacceptable delays for biometric systems has been to add a non-biometric discriminator that converts one-to-many verification tasks to one-to-one. Although effective, combining biometric and non-biometric systems is not desirable for the reasons stated herein above.
Although many inventors have devised myriad approaches attempting to provide inexpensive, minimally invasive, and fast fingerprint verification systems in which fingerprints of human users could be stored, retrieved and compared at some later time to verify that a human user is indeed a properly authorized user, none have succeeded in producing a system that is practical and desirable for use in security applications requiring one-to-many biometric verification. Because of these and other significant imitations, commercially viable biometric-based security systems have slow in coming to market.
The present invention overcomes all of the aforesaid imitations by combining a very fast and streamlined facial image-based search engine with state-of-the-art fingerprint verification algorithms. The present invention allows fingerprint verification analysis to be utilized in one-to-many applications by first reducing the problem to one-to-few. The facial image-based search engine can rapidly order a user database which then permits the fingerprint verification engine to search in a heuristic fashion. Often, after a database has been so organized based on facial image recognition, less than 10 fingerprint comparisons are necessary to find the authorized user. In reference to the example described herein above, even with a 2000 user database, the fingerprint algorithm would only need to compare ten individual fingerprints to find a match. Thus instead of a 3 minute processing delay, any given individual in the database would likely only experience a one second processing delay. This novel utilization of one biometric to provide a heuristic search method for another biometric allows the creation of a truly practical “pure” biometric security system